The 2025 Nobel Prize in Economics: Explained

0:00 The Spherigus Riksbank Prize in Economic Sciences in Memory of Alfred Nobel,

0:03 more commonly known simply as the Nobel Prize in Economics,

0:06 was awarded this year to these three gentlemen.

0:09 Half of the roughly 1.1 million USD prize went to Joel Mochir,

0:12 with the other half being shared between Philip Azion and Peter

0:15 Howard for their combined work on explaining innovation driven economic growth.

0:18 We will get to the reason why they split the prize up like this soon,

0:22 but for now of course, while this is a lot of money,

0:24 the real prize for these recipients is the recognition of a lifetime of work

0:27 that is widely to be accepted as the highest honour in the field of economics.

0:31 To earn this prize, what these three economists

0:33 have shown is that the sustained growth experience

0:36 over the last two centuries and the prosperity

0:38 that's come with it was pushed by technological innovation.

0:41 Since the Industrial Revolution,

0:43 new technologies have given us more advanced products

0:46 and production methods leading to higher economic output,

0:48 more wealth and better living standards for billions of people across the world.

0:52 Now, perhaps understandably, there's got a lot of people thinking,

0:55 the Industrial Revolution and new technologies contributed

0:57 to higher economic growth, uh, no shit.

0:59 Ask anybody with even a passing interest in history or economics

1:02 and they would probably tell you roughly the same thing, right?

1:05 Well, yes, but the thing that made the work of these three

1:09 men Nobel Prize worthy was first

1:10 identifying that constantly compounding technological progress

1:13 is actually something of an anomaly rather than the expectation and they

1:17 also analytically unpacked what exactly is needed to keep this process going.

1:21 Now, as always, even though they will say it was complete coincidence,

1:24 this year's prize is incredibly relevant to a lot

1:27 of challenges in the global economy today,

1:29 from the disruptions that could be caused by AI to the stifling

1:32 of innovation by companies that no longer need to compete.

1:35 Understanding the work of these men can help us

1:37 understand exactly what has made the world hundreds of times

1:40 wealthier than it was just a few generations ago

1:42 and the threats that we face to that progress going forward.

1:46 So, what was it that enabled technological

1:48 innovation to compound on itself so rapidly?

1:50 Is this progress always a good thing?

1:53 And finally, are we starting to lose those magic

1:55 ingredients that made it all possible in the first place?

1:58 Once we have done all of that, it's probably worthwhile

2:00 addressing some of the controversies surrounding this year's prize as well.

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3:07 Starting around 1760,

3:08 the Industrial Revolution has made the world hundreds of times

3:12 wealthier in a relative blink of the eye by historical standards.

3:15 Not only are people on average far wealthier

3:17 today than they were just a few generations ago, but there are also far more

3:21 people overall since technologies like mechanized farming,

3:23 soil science, and even basic stuff like

3:26 pumped water have supported far larger populations.

3:28 Beyond that, this wealth can also be used to consume

3:31 goods and services that just weren't possible before the Industrial Revolution.

3:35 The wealthiest kings from the Middle Ages couldn't buy modern medicine

3:38 or even modern conveniences that most of us take for granted today.

3:42 Now, the foundation of this progress was, of course, technology.

3:45 But the first misconception that this year's Nobel laureates challenged

3:49 was that technological innovations rarely

3:51 happened before the Industrial Revolution.

3:53 In reality, they happened all the time.

3:55 The printing press and naval architecture,

3:57 advanced navigation, new tools, clockwork, farming techniques,

4:00 even medical advancements happened more frequently than

4:03 most people give the pre-industrial world credit for.

4:05 The problem was that none

4:07 of these advancements really translated into sustained economic

4:09 growth like they do today or any time over the last 200 years.

4:13 So the question became, why not?

4:16 Well, Mokir, an economic historian and the winner of half of this year's prize,

4:21 spent years researching and explanation.

4:22 He actually found that certain pre-industrial

4:24 empires were more inventive than others,

4:26 but despite this, they weren't measurably better off.

4:29 The reason he found was that over time

4:31 people were very good at finding things that worked,

4:34 but they weren't very good at figuring out why they worked.

4:37 He almost poetically put it that before the Industrial Revolution,

4:40 he was a world of engineering without mechanics, iron making without metallurgy,

4:44 farming without soil signs,

4:46 mining without geology, water power without hydraulics,

4:49 dye making without organic chemistry,

4:50 and medical practice without microbiology or immunology.

4:53 People stumbled upon tools and techniques that worked,

4:56 but without understanding why they worked,

4:59 they couldn't make consistent improvements on it,

5:01 so they would eventually just hit another plateau.

5:05 Material science for example,

5:07 pre-industrial blacksmiths were very adept at forging different metals,

5:10 but they didn't understand the molecular changes that they were causing,

5:13 so they couldn't make informed improvements

5:15 beyond just straight trial and error.

5:17 Sustained economic progress as it turned out required

5:18 more than just a prayer to the machine god.

5:21 Yes, I know you were thinking it ever since I said the word adept.

5:24 But anyway, pre-industrial smiths might have

5:26 figured out that forging iron over coal

5:28 or charcoal gave it a harder edge and made it more resistant to corrosion,

5:31 but they didn't understand that this was because carbon

5:34 was getting into the crystalline structure of the metal,

5:36 and because they didn't understand that, they were limited to trial

5:38 and error when it came to things like developing different steel alloys,

5:41 which have in turn become some

5:43 of the most important materials in the modern world.

5:46 We really couldn't run our modern global economy

5:48 without a selection of different types of steel,

5:50 but of course this was just one example.

5:53 Knowledge without understanding also made it hard to invest into new ideas.

5:57 Without a realistic foundation of scientific understanding,

6:00 investing in a new way to make stronger steels was functionally no

6:03 different from investing in a new way to turn lead into gold.

6:06 Both sounded equally crazy.

6:08 So then, what exactly changed to kick off the industrial revolution?

6:12 The common understanding is that eventually we just hit

6:15 a critical mass of innovation and it took off from there.

6:18 More specifically, some people might point to the steam

6:20 engine as well the engine of early industry,

6:22 but Machia challenged that assumption and instead proposed

6:25 that it was societal changes that facilitated this development.

6:28 One of those changes was bringing people with theoretical

6:31 knowledge into more contact with people who had practical skills.

6:35 The ancient Greeks, for example,

6:36 had incredibly sophisticated thinkers in fields like mathematics,

6:39 but those people really interacted with builders or laborers,

6:42 so the blending of theory and practice never

6:45 really had much of an opportunity to take place.

6:48 The Enlightenment across Europe in the 1700s

6:50 brought these two groups closer together and allowed

6:52 these ideas to actually go back and forth for the first time in history.

6:56 In the UK in particular, this was accelerated by a robust system

6:59 of apprentice tradesmen who could learn both

7:01 theory and practice and then in turn teach that to their own young padawans.

7:05 Understanding an application coming together is what has

7:08 made the world as wealthy as it is today,

7:10 but there was also something else important that had

7:12 to happen to make way for this progress.

7:14 This part was the other half of the overall

7:16 prize which was awarded to Ajeon and Howard.

7:19 Overall progress over the last 200 years

7:21 on a macroeconomic level looks incredibly smooth and consistent,

7:24 but beneath the surface it relied

7:27 on an almost constant churning of next best ideas.

7:29 Water wheels and horses made way for steam engines which made way for internal

7:33 combustion engines and were currently living

7:35 through their dominance been challenged by electrification.

7:37 For new innovations to succeed,

7:39 economies need to create environments where outdated industries can fail.

7:43 The Roman Empire had many great thinkers who invented

7:46 a lot of very promising technologies including even rudimentary steam engines.

7:50 Now there were some technical problems with these early designs,

7:53 but there also wasn't a huge motivation to improve

7:55 them beyond little curiosities because well the powers

7:58 that be in the empire didn't need steam

8:00 engines when they could just buy more slaves.

8:02 Obviously that is an extreme example,

8:04 but on a small scale this process of what economists

8:07 call creative destruction has happened

8:09 very consistently since the industrial revolution.

8:11 What Ajeon and Howard created was a mathematical framework

8:14 by which to measure how this translates into economic growth.

8:18 In extremely basic terms they surmise that the rate of economic growth was

8:22 the product of the scale of innovations

8:24 multiplied by how often those innovations came about.

8:26 Now the actual equations they published were a little bit more uh Greek,

8:30 but this is basically what they meant.

8:33 We can't necessarily guarantee that every innovation we make is

8:36 going to push the world ahead by a significant margin.

8:39 For every iPhone there is a metaverse.

8:40 What we can control through economic policy though

8:43 is the rate of new innovations by encouraging

8:45 organizations to invest into research and development

8:48 through a combination of both carrots and sticks.

8:50 On one side if an individual

8:52 or a company creates or invents something with significant

8:55 economic value they should be allowed to profit

8:57 off that value with enforced intellectual property protections.

9:00 This creates a profit motive for innovation

9:03 which not only incentivizes people to get out

9:05 there and try improving the world it also

9:07 makes it easier for those innovators to get

9:09 investment funding to pursue those innovations because

9:11 the people who invest in them will have

9:13 the potential to share in the profits they

9:15 will receive from bringing so dominant in the market.

9:17 The clearest example of something like this right now

9:20 and perhaps the clearest example in history is Nvidia.

9:22 They invested tens of billions of dollars and many years into developing CUDA,

9:26 their proprietary platform for parallel computing,

9:28 which is what has made their chips

9:30 the industry standard today for artificial intelligence.

9:32 They are allowed to have the market dominance and make

9:35 the massive profits that come with it and hopefully other

9:37 companies will see this and also be motivated to make

9:40 decades long investments that may or may not pay off.

9:43 However, if this market dominance goes too far or competitors

9:46 are allowed to get too cozy with one another

9:49 it will stifle the same innovation because it becomes

9:52 easy to discharge customers more without having to actually compete.

9:55 What their models showed was that there was an inverted

9:58 U-curve of economic innovation depending on how competitive the market was.

10:01 If the market is just insanely cutthroat with every company stealing every

10:05 other company's designs and ideas and relentlessly

10:07 undercutting one another all the time,

10:09 that would be good for consumers for a little while.

10:12 However, nobody would be willing to innovate because

10:14 there would be no profit motive to do so.

10:17 Likewise, if companies just collude on price

10:19 or the market is an uncontestable monopoly,

10:22 they also won't innovate because new technology could

10:24 threaten their lead and just represent an unnecessary expense.

10:27 The solution to maximizing innovation was to create economic policies

10:31 that made a little bit of market dominance possible through

10:34 protecting intellectual property but also avoided too much dominance through

10:37 trust-busting and limiting how long IP would be protected for.

10:40 Now, in their models, Azion and Howard were primarily studying

10:44 profit-driven corporations in modern capitalist market systems.

10:47 But Makir and other economists would probably argue

10:50 that the same general rules apply to something like pre-industrial nobility.

10:54 They effectively had what amounted to market dominance over their economies,

10:58 so if anything, new technologies just represented

11:00 a threat to their comfortable status quo.

11:02 Creative destruction may be the driver of innovation,

11:05 but if the organizations that are going

11:07 to be creatively destroyed have any say over it,

11:09 they're probably going to try their best to stop it.

11:12 This was actually one of the most important components

11:14 of their work and something that's

11:15 become incredibly important in today's economy.

11:17 So the not-so-subtle theme of this year's

11:20 prizes was the science surrounding artificial intelligence.

11:22 Now, we'll get to the controversy soon enough,

11:25 but for what it's worth, the work of Makir,

11:28 Azion and Howard is going to be incredibly useful for shaping policy around AI.

11:32 Now, nobody can predict the future least of all economists,

11:36 but there are some takeaways that should be clear from this work.

11:40 For starters, AI is obviously yet another technological innovation

11:43 which has the potential to fuel further economic growth,

11:45 but depending on the interpretation of the work of these men,

11:48 it could also be much more than that.

11:51 Remember, sustained economic advancement was

11:52 enabled when people with theoretical

11:54 knowledge engaged more actively with people who had practical knowledge.

11:57 An optimistic interpretation of this technology could be that it

12:01 makes theoretical knowledge even more accessible to average workers,

12:04 making more advancements possible,

12:06 but their work also addressed some of the less

12:09 optimistic aspects of a potential AI future.

12:11 In this case, the industry that is

12:14 potentially getting creatively destroyed are the workers themselves.

12:16 Obviously, it's not there yet, but a lot of people are rightfully afraid

12:21 of being the equivalent of a water wheel,

12:23 right as engineers are playing around with early steam engines,

12:26 which is where we get back to that final

12:28 and perhaps most important component of their work,

12:31 which is that there should be robust protections in place

12:33 for people who are displaced by the process of creative destruction.

12:36 Now, this is not just because it's a nice thing to do,

12:40 or because long-term unemployment amongst large swathes

12:42 of the population could cause social problems,

12:45 it's because it's just good economics.

12:48 If people aren't terrified of disruption,

12:50 it can encourage the risk-taking needed to cultivate these innovations

12:53 and also make sure that there is more popular support for it.

12:57 Today, there is a lot of resistance to AI and some good reasons for it.

13:01 The immense capital that has been dedicated to building out data centres,

13:04 the energy requirements to power them,

13:06 and the investment money surrounding it, which let's be real, average taxpayers,

13:09 are probably going to have to bail out if it all collapses.

13:13 However, if we are being honest,

13:14 the biggest source of animosity towards this technology is

13:17 coming from people who think it will take their jobs.

13:20 The Laureates identified this with their work and pointed to countries like

13:23 Denmark and the Netherlands for their labour force to find by flex security,

13:26 with the idea being that people are actually fairly easy to fire from a job,

13:30 but when they are, they will be covered

13:32 through generous welfare and retrained into more in-demand skills.

13:35 This also means that workers are easier to hire because there

13:38 is less risk of them becoming an ongoing burden on the business.

13:42 Even before the current hubbub around AI,

13:44 these gentlemen highlighted the importance of social insurance

13:47 to lubricate the process of innovation through creative destruction.

13:50 Now, these were the headline takeaways from their work

13:52 in the context of the AI revolution,

13:54 but to roleplay as English lit majors for a second

13:57 and look for deeper meaning where there is none,

13:59 there is probably more to analyse here.

14:00 It's important to remember that the Nobel Prize

14:03 is awarded for work that can span decades.

14:05 This year's winners were publishing a lot of their work in the early 1990s,

14:09 so they obviously weren't specifically studying

14:11 modern machine learning and its impacts.

14:13 However, even still,

14:14 their work around the dynamics of intellectual property rights

14:17 are probably more relevant today than they ever have been.

14:21 AI has really tested the limits of how we use the intellectual

14:24 creations of others and in what capacity others can profit off them.

14:28 Again, beyond just the fairness argument,

14:29 if people can't make a living by creating new things because

14:32 it just gets yoinked off them and ingested into training data,

14:35 they won't create anything anymore.

14:37 This is bad for economic progress, let alone society at large,

14:40 so even though it wasn't specifically intentional,

14:42 the work of this year's Nobel laureates really highlights

14:45 how important regulation is going to be around these issues.

14:49 Oh, and the committee almost certainly didn't mean it,

14:52 but giving the award to Mokir who

14:54 went back through history to critique the shortcomings

14:56 of knowledge without understanding in a year

14:58 of awards centred around AI is just unintentionally brilliant.

15:01 But that probably leads us along well

15:04 to the controversies surrounding this year's prize.

15:06 For starters, there was the alleged leaks of the winners of the Peace Prize,

15:10 leading to several large bets being

15:12 placed shortly before the announcement was made.

15:14 Now this is a bad look for the awards committee,

15:17 but probably a worse indictment on society at large.

15:19 Stop turning everything into a casino when

15:22 these kinds of fraudulent opportunities wouldn't exist.

15:24 But beyond that, there are deeper issues with the structure

15:26 of the prize itself that are worth addressing.

15:28 Big disclaimer time, I want to be very delicate with how I approach this part,

15:33 because by no means am I in any way trying to suggest that any

15:36 of the winners in the scientific categories were not worthy of this prize.

15:40 In the field of economics, these three men are absolutely brilliant,

15:43 and from my admittedly limited understanding of the other fields,

15:46 so is everybody else who won these year's prizes.

15:49 However, the template of the prize itself is getting harder

15:53 and harder to reconcile with how modern science gets done.

15:56 The lone genius single-handedly making major

15:58 breakthroughs doesn't really happen that much anymore.

16:01 Some research involves collaboration between

16:03 dozens or even hundreds of scientists, but a Nobel Prize can only be awarded

16:07 to a maximum of three recipients in a given year.

16:10 Now this is not as big a problem

16:12 in economics where research teams are still generally quite small,

16:15 but for, well, real sciences like physics and chemistry,

16:18 it's getting very hard to pick out winners from amongst their peers.

16:22 Additionally, and quite ironically given

16:24 this year's focus on compounding discoveries,

16:26 the Nobel Prize is not awarded posthumously.

16:29 As science has matured, we are increasingly standing on the shoulders of giants.

16:33 For all the focus on creative destruction in this year's prize,

16:36 none of these men discovered this process.

16:39 Creative destruction was described and studied

16:41 almost a hundred years ago by Schumpeter,

16:43 Sombart, and to really add layers to this controversy, Marx as well.

16:46 The challenges of the modern prize also expand

16:49 to the scope of what science covers as well,

16:52 which has clearly changed a lot since the prize was first established.

16:56 For starters, economics was never one

16:57 of the original categories to receive this award,

17:00 which is why it's technically the Spherigas Riksbank

17:02 Prize in Economic Sciences in memory of Alfred Nobel,

17:04 not just the Nobel Prize in Economics.

17:07 But potentially, they may need to expand this further.

17:09 Last year, the prize in physics was awarded to Hopfield

17:13 and Hinton for their contributions to machine learning and neural networks.

17:17 Obviously important stuff,

17:19 but people were not happy because this wasn't really traditional physics.

17:22 It was computer science,

17:24 something that there clearly isn't a Nobel Prize for because,

17:27 well, computers didn't exist back when the foundation was created.

17:30 Either way, this shouldn't detract from the well-deserved recognition

17:33 of this year's winners amongst all of the fields,

17:35 but it's probably worth addressing if for no other reason than

17:38 to add some context to the people writing off the prizes entirely.

17:41 It's also a good opportunity to repeat

17:43 that most science is done collaboratively between

17:46 big groups of very talented people who

17:48 will never get the recognition they really deserve.

17:50 It's nice that prizes like this exist,

17:52 but they certainly can't be the motivation for any career in these fields.

17:56 Now, if you want to learn about last year's winners,

17:58 we've made a playlist explaining all of the economic prizes back to 2022,

18:01 which you should be able to click to on your screen now.

18:04 Thanks for watching, mate.

18:06 Bye.